elyadenysova
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Irony_DistilBert

Text Classification

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Irony_DistilBert

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 0.8133
eval_accuracy: 0.7105
eval_runtime: 3.4292
eval_samples_per_second: 228.622
eval_steps_per_second: 14.289
step: 0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

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Safetensors

Model size

67M params

Tensor type

F32

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Base model

distilbert/distilbert-base-uncased

Finetuned

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Evaluation results

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